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Discovering Web access patterns and trends by applying OLAP and data mining technology on Web logs

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3 Author(s)
O. R. Zaiane ; Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC, Canada ; Man Xin ; Jiawei Han

As a confluence of data mining and World Wide Web technologies, it is now possible to perform data mining on Web log records collected from the Internet Web-page access history. The behaviour of Web page readers is imprinted in the Web server log files. Analyzing and exploring regularities in this behaviour can improve the system performance, enhance the quality and delivery of Internet information services to the end user, and identify populations of potential customers for electronic commerce. Thus, by observing people using collections of data, data mining can bring a considerable contribution to digital library designers. In a joint effort between the TeleLearning-NCE (Networks of Centres of Excellence) project on the Virtual University and the NCE-IRIS project on data mining, we have been developing a knowledge discovery tool, called WebLogMiner, for mining Web server log files. This paper presents the design of WebLogMiner, reports current progress and outlines future work in this direction

Published in:

Research and Technology Advances in Digital Libraries, 1998. ADL 98. Proceedings. IEEE International Forum on

Date of Conference:

22-24 Apr 1998